Superposition/puncturing is considered a promising option to allocate the URLLC traffic due to the tolerance of the latter in terms of latency and reliability. Hence, much work [1]}, [2]}, [3]}, [4]}, [5]}, [6]}, [7]}, [8]} focused on developing techniques based on coupling URLLC and conventional (eMBB) data transmission through superposition/puncturing. In [1]}, [2]}, [3]}, [4]}, [5]}, [6]}, [7]}, [8]}, the authors investigated and developed novel superposition/puncturing approaches aiming to minimize the impact on eMBB in terms of the contaminated symbols. The advantages of using superposition for sharing resources in uplink communications between eMBB,
mMTC, and URLLC devices was studied in [1]}. For URLLC downlink MIMO-NOMA, network layer performance bounds
and cross-layer power control were studied in [2]}.
A max-matching diversity (MMD) algorithm was proposed in [3]} to allocate eMBB users, considering both heterogeneous orthogonal and non-orthogonal multiple access network slicing strategies. A machine learning approach for hybrid multiple access solution (HMA) was proposed in [4]}. In fact, the classical methods of NOMA, such as power-domain, require perfect channel state information (CSI) at the BS such that the transmitted signal can be separated at the receiver with successive interference cancellation (SIC)[21]}. A new class of NOMA, namely bits similarity NOMA, was proposed in [21]}. It was shown that, without perfect CSI, bit-similarity NOMA can achieve better spectral efficiency and fairness among users compared to traditional NOMA techniques. In fact, superposition techniques (NOMA) cause severe degradation to the URLLC reliability because the eMBB signal acts as an interference signal that increases the decoding errors of the URLLC traffic. Moreover, the lack of the URLLC CSI at the transmitter decreases the chances to superpose URLLC traffic on eMBB [23]}. Thus, puncturing is preferred as it conserves URLLC reliability.
